Abstract
In order to help the forging enterprise realize energy conservation and emission reduction, the scheduling problem of furnace heating was improved in this paper. Aiming at the charging problem of continuous heating furnace, a multi-objective furnace charging model with minimum capacity difference and waiting time was established in this paper. An improved strength Pareto evolutionary algorithm 2 (SPEA2) algorithm was designed to solve this problem. The original fitness assignment strategy, crossover operator and population selection mechanism of SPEA2 are replaced with DOPGA (Domination Power of an Individual Genetic Algorithm), adaptive cross operator, and elitist strategy. Finally, the effectiveness and feasibility of the improved SPEA2 was verified by actual arithmetic example. The comparison of results gained from three methods shows the superiority of the improved SPEA2 in solving this problem. Compared with strength Pareto evolutionary algorithm (SPEA) and SPEA2, the improved SPEA2 can get a better solution without increasing time complexity, the heating time is reduced by total 93 min, and can save 7533GJ energy. The research in this paper can help the forging enterprise improve furnace utilization, reduce heating time and unnecessary heating preservation time, as well as achieve sustainable energy savings and emissions reduction.
Highlights
The forging stock heating process suffers significant energy consumption
It is very valuable to carry out energy-saving scheduling research for the forging stock heating process
Studies about heating furnace energy conservation are mainly focused on equipment optimization and reform [1], waste gas heat recycling and utilization [2], development and application of new materials [3,4,5], improvement of heat treatment process [6,7], etc
Summary
The forging stock heating process suffers significant energy consumption. Except for discrete energy consumed in forging and machining operations, the consumption of all continuous energy (heat energy) comes from the heating furnace. With respect to the process of a forging stock charging furnace, Zhu et al [13] studied the combination optimization problem on the charging furnace, but this model is relatively simple, and they failed to consider the problem that heating standards vary for different shapes and sizes. The forging charging sequence shall be scheduled based on these two parameters so as to reduce unnecessary energy consumption and, promoting the forging enterprise more in line with low-carbon sustainable economic development Focusing on this problem, and taking the influence of shape and size on the utilization of the furnace as the starting point, the research on scheduling for the forging stock’s charging process was carried out in this paper
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